CN105978615A - Multi-cell large-scale MIMO interference elimination method based on antenna selection and interference alignment - Google Patents

Multi-cell large-scale MIMO interference elimination method based on antenna selection and interference alignment Download PDF

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CN105978615A
CN105978615A CN201610325499.2A CN201610325499A CN105978615A CN 105978615 A CN105978615 A CN 105978615A CN 201610325499 A CN201610325499 A CN 201610325499A CN 105978615 A CN105978615 A CN 105978615A
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base station
vector
interference alignment
interference
channel matrix
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CN105978615B (en
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杨全校
杨海芬
林水生
周亮
袁强
尹腾飞
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University of Electronic Science and Technology of China
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/0413—MIMO systems
    • H04B7/0426—Power distribution
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/0413—MIMO systems
    • H04B7/0456—Selection of precoding matrices or codebooks, e.g. using matrices antenna weighting
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/06—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/06—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station
    • H04B7/0602—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using antenna switching
    • H04B7/0608—Antenna selection according to transmission parameters

Abstract

The invention discloses a multi-cell large-scale MIMO interference elimination method based on antenna selection and interference alignment, and belongs to the technical field of mobile wireless communication. The method comprises the steps: enabling a base station to obtain a channel matrix, respectively calculating the norm of a column vector corresponding to each transmitting antenna, selecting the former Ns antennas with the maximum norms as active antennas, and turning off other antennas; enabling the columns vectors corresponding to the active antennas to serve as a new channel matrix, calculating the interference alignment precoding vector of each base station, calculating a receiving zero-forcing vector of each receiving end according to the interference alignment precoding vectors and the new channel matrix, and updating the receiving zero-forcing vectors based on transmitting power; finally enabling a current base station to generate transmission data corresponding to a receiving end based on the interference alignment precoding vector, the current receiving zero-forcing vector and the transmitting power of each data flow, and transmitting the transmission data. According to the embodiment of the invention, the method can reduce the calculation complexity, improves the transmission rate, and reduces the bit error rate.

Description

Based on sky line options and the multiple cell extensive MIMO interference elimination method of interference alignment
Technical field
The invention belongs to mobile radio telecommunications technical field, particularly to a kind of many based on sky line options and interference alignment Community extensive MIMO interference elimination method
Background technology
Extensive MIMO technology, by base station end configure substantial amounts of antenna can significantly improve system spectrum efficiency and Efficiency efficiency, when antenna for base station number tends to infinite, the channel matrix between different user tends to orthogonal, such that it is able to eliminate Inter-user interference and presence of intercell interference, thus receive and study widely and pay close attention to.But, the number of antennas in practical situation is not May be infinite many, the channel matrix between different user is not that ideal quadrature, i.e. inter-user interference still exist, especially Cell Edge User.
Interference alignment techniques, is to utilize, at transmitting terminal, the channel condition information design pre-coding matrix having learned that so that Interference signal aligns at receiving terminal, thus has obtained glitch-free desired signal, have compressed the son shared by interference signal empty simultaneously Between, increase the dimension of desired signal, improve the transfer rate of system.Interference alignment algorithm is generally divided into linear disturbance at present Alignment and iteration interference alignment, and the former has certain advantage owing to computation complexity is relatively low in reality application.
Antenna Selection Technology is according to certain criterion, selects a portion antenna to carry out from all of service antenna Signal is launched.Antenna selection criterion can be maximum channel capacity criterion, and maximum signal noise ratio principle and minimum bit-error rate are the most accurate Etc..In systems in practice, it is contemplated that actual physics limits, it is achieved the factor such as complexity and cost, the antenna of substantial amounts can Can become the bottleneck of Project Realization.By Antenna Selection Technology can effectively reduce system signal process complexity with become This, and remain most premium properties that large-scale antenna array is brought to a certain extent, it is possible to achieve on big rule Mould mimo system performance and the effective of complexity trade off.
Power distribution is one of content of resource distribution, carries out power distribution according to actual channel conditions and can improve communication The performance of system, such as water-filling algorithm are so that the channel capacity of mimo system maximizes.Distribute discounting for power, i.e. Constant power distributes, it will makes the efficient channel gain serious unbalance of each data stream transmitted, is difficult to make the performance of system Reach optimum.Document " Interference Alignment Based On Antenna Selection For Massive MIMO System”(Zhiyuan Shi,Xiaopeng Zhu,Yifeng Zhao,Lianfen Huang,Computer Science&Education(ICCSE),2015 10th International Conference on,22-24July 2015, pp.606-610) combine in extensive mimo system have employed day line options and interference alignment techniques to eliminate interference, But the problem not considering power distribution, and the complexity of Antenna Selection Algorithem is higher, and systematic function still has bigger Room for promotion.
Summary of the invention
The goal of the invention of the present invention is: for the problem of above-mentioned existence, it is proposed that a kind of based on sky line options, it is right to disturb The extensive MIMO interference elimination method that neat and dynamic power distributes, it utilizes interference alignment techniques to be greatly improved user's Transfer rate and performance of BER, reduce channel matrix dimension by Antenna Selection Technology simultaneously, thus reduce computing Complexity, beneficially Project Realization.
The multiple cell extensive MIMO interference elimination method alignd based on sky line options and interference of the present invention, including following Step:
Step 1: base station end obtains the channel condition information CSI of all users by ascending pilot frequency, i.e. obtains channel matrix Hij∈CN×M(CN×MRepresent N × Metzler matrix), wherein HijRepresenting the channel matrix of user j to base station i, M represents the antenna of base station end Number, N is the number of antennas of user side.
Step 2: in each base station, according to the channel square of the user that channel capacity maximization criterion and base station are each serviced Battle array carries out a day line options.The criterion of described antenna selection gist is:Wherein φ represents base Stand the antenna subset selected by end, hiRepresent the column vector launched corresponding to antenna i.Calculate channel matrix H the most respectivelyiiAll The norm of column vector, selects the front Ns root antenna of norm maximum as active antenna, and Ns is required selection number of antennas, and closes Residue M-NsRoot antenna.
Step 3: base station end redefines the channel matrix of actual employing according to the result of step 2 day line options, for often One channel matrix Hij, select Ns row column vector therein as new channel matrix H _ asij, i.e. H_asij=[hijk]k∈φ, Wherein, [hijk] represent channel matrix HijKth row.
Step 4: base station end is according to the channel matrix H _ as after sky line optionsijCalculate interference alignment precoding vector.
Interference alignment schemes of the present invention is described in step 401-403:
401: to confederate matrixCarrying out Eigenvalues Decomposition, selected characteristic value is maximum D (D be send number of data streams) row characteristic vector align precoding vector v as the interference of base station 11Row vector of going forward side by side is returned One change processes；I.e. v1(:, r)=v1(:,r)/||v1(:, r) | |, r=1 ..., D, symbol (:, r) expression takes r column operations
402: according to formulaThe interference alignment precoding vector v of calculation base station 22Row vector of going forward side by side is returned One change processes；
403: according to formulaThe interference alignment precoding vector v. of calculation base station 33Go forward side by side row vector Normalized.
Step 5: null vector is compeled in the reception calculating receiving terminal.
Described ZF processes the urgent null matrix used and obtains according to following equation:
wj=U_Hj((j-1)*D+1:j*D,:)
Wherein, wj(D is the number of data streams that user j sends, and N is user j to compel null matrix for the reception of the user j of D × N Number of antennas), i.e. wjIt is made up of wherein corresponding d every trade vector,Transmission channel matrix, U_H is combined for equivalencejFor equivalence The pseudo inverse matrix of confederate matrix, ()HThe conjugate transpose of representing matrix, lower same.
Step 6: calculate the reception ZF matrix column vector field homoemorphism value of each user respectively, and enter according to the size of modulus value Mobile state power distributes:
First calculate the ZF vector field homoemorphism value vector of user jWherein symbol diag (A) Represent the diagonal element taking matrix A.
The transmit power carrying out data stream further according to modulus value is distributed:Wherein, P represents all The total emission power of base station, pjrRepresent that current base station launches the power of r flow data, d to user jjrRepresent r of user j ZF vector field homoemorphism value, i.e. matrix djJth row corresponding to modulus value,
Step 7: update according to current power distribution condition and compel null matrix:Wherein pj=diag (pj1,pj2,...,pjD).Step 8: the result of calculation combining above-mentioned sky line options, interference alignment and power distribution generates transmission Data: xj=vi*pj*sj, wherein xjRepresent that current base station sends data vector, p to N × 1 of user jjFor current base station about The power distribution diagonal matrix of user j, diagonal element is the power p of each data stream distributionjr, sjFor being sent to the former of user j Originate and send data.
In sum, owing to have employed technique scheme, the invention has the beneficial effects as follows: compared with prior art, this Invention reduces channel matrix dimension by antenna selecting method, so that available relatively low complexity achieves big rule The interference of mould mimo system eliminates, and improves the transfer rate of user, is reduced the mistake ratio of system simultaneously by dynamic power distribution Special rate performance, improves the reliability of system transfers.
Accompanying drawing explanation
Fig. 1 is embodiments of the invention scene schematic diagrams.
Fig. 2 is the enforcement structured flowchart of the embodiment of the present invention.
Fig. 3 by the taked Antenna Selection Algorithem of the present invention the fade algorithm optimal with performance up to rate correlation curve.
Fig. 4 is the performance of BER correlation curve under case study on implementation 4 antenna case of the present invention.
Fig. 5 is the performance of BER correlation curve under case study on implementation 8 antenna case of the present invention.
Fig. 6 be under case study on implementation 4 antenna case of the present invention up to rate correlation curve.
Fig. 7 be under case study on implementation 8 antenna case of the present invention up to rate correlation curve.
Detailed description of the invention
For making the object, technical solutions and advantages of the present invention clearer, below in conjunction with embodiment and accompanying drawing, to this Bright it is described in further detail.
Embodiment
Seeing Fig. 1, the system scenarios of this example is extensive MIMO multi-cell system based on C-RAN framework, and system is adopted Use TDD standard.The channel information of shared all communities that can be the most no-delay under C-RAN framework, substantially increases connection The exploitativeness that conjunction processes.3 communities, base station, one, each community, one community of service, each base station is considered in present case Edge customer, the number of antennas of base station end is 128, and the number of antennas of user side is N, N takes in this example 4 and 8 and emulates Analyze.Channel condition information in the present embodiment is zero-mean, and variance is the multiple gaussian variable of 1.The transmitting total work of all base stations Rate is P.
For above-described embodiment, it is extensive with what interference alignment and power distributed based on sky line options that the present invention provides The step that implements of MIMO interference elimination method is:
Step S1: base station end obtains the channel condition information CSI of all users by ascending pilot frequency, i.e. obtains channel matrix Hij∈CN×128, i, j=1,2,3, wherein HijRepresent the channel matrix of user j to base station i.
Step S2: in each base station, according to the channel square of the user that signal to noise ratio maximization criterion and base station are each serviced Battle array Hii, i=1,2,3 carries out a day line options.
I.e. according to formulaM=128, calculates channel matrix H respectively11,H22And H33 The modulus value of all column vectors, select the N root antenna that wherein modulus value is maximum as active antenna, close residue 128-N root antenna.
Step S3: base station end redefines the channel matrix of actual employing according to the result of step S2 days line options, for Each channel matrix, selects N row column vector therein as new channel matrix H _ asij。
H_asij=[hijk]k∈φWherein, [hijk] represent channel matrix HijKth row.
Step S4: base station end is according to the channel matrix H _ as after sky line optionsijCalculate interference alignment precoding vector vi.First First to confederate matrixCarry out Eigenvalues Decomposition, N/2 (this reality that selected characteristic value is maximum Executing in example, number of data streams D of transmission is N/2) row characteristic vector as base station 1 interference align precoding vector v1, and root According to formula v1(:, r)=v1(:,r)/||v1(:, r) | |, r=1 ..., N/2 carries out vector normalized；Then according to formulaThe interference alignment precoding vector v of calculation base station 22Row vector of going forward side by side normalized；Finally according to public affairs FormulaThe interference alignment precoding vector v of calculation base station 33Row vector of going forward side by side normalized.
Step S5: null vector is compeled in the reception calculating receiving terminal.
First basis Calculate U_Hj, further according to wj=U_Hj((j-1) * D+1:j*D :), j=1,2,3 obtains the reception of user j and compels null matrix wj, i.e. wj By U_HjThe N/2 every trade vector composition of middle correspondence.
Step S6: calculate the reception ZF matrix column vector field homoemorphism value of each user respectively, and according to modulus value number According to the transmit power distribution of stream, i.e.Wherein djrZF vector field homoemorphism value vector d for user jj R row modulus value, T is all user's ZF vector field homoemorphism value sums.
Step S7: update according to power allocation case and compel null matrix.EvenWherein
Step S8: current base station end combines the result of calculation of above-mentioned sky line options, interference alignment and power distribution and generates About originally transmitted data sjTransmission data xj: xj=vi*pj*sj。
Step S9: receiving terminal docking collection of letters yjCarry out ZF and process the transmission data that can get correspondence, i.e. yj= wj*rj, wherein rjReception vector for N × 1.
In order to assess the performance of the present invention, use Monte Carlo simulation method that channel capacity and bit error rate are imitated Very.
Fig. 3 be the Antenna Selection Algorithem that uses of the present invention algorithm that fades with best performance up to rate correlation curve, its Middle QPSK represents orthogonal frequency shift keying, and AS represents a day line options, and IA represents interference alignment, and ZF represents ZF precoding, and MF represents Matched filtering precoding.It will be seen that the channel coefficients assumed at this example is zero-mean, variance is the multiple gaussian variable of 1 Under scene, the simple Antenna Selection Algorithem that the present invention is taked is relative to the channel capacity of the algorithm that fades, when low signal-to-noise ratio Performance is almost consistent, and only has the performance loss of about 1-2bps/Hz under high s/n ratio when 4 antenna, only has about 2-when 8 antenna The performance loss of 3bps/Hz.The Antenna Selection Algorithem complexity that the present invention is taked is then low many, and beneficially engineering is real Existing.The Antenna Selection Algorithem that the present invention is taked only needs calculate the modulus value of the transmission vector corresponding to every transmitting antenna and take it The Ns root that middle modulus value is maximum, and channel capacity maximizes the algorithm that fades and needs to carry out N-Ns iteration, each iteration needs to calculate Removing channel capacity performance loss produced by every antenna, the sky line options that complexity is substantially higher in the present invention is taked is calculated Method.
Fig. 4 and Fig. 5 be algorithms of different performance of BER contrast, it can be seen that the present invention invent proposition based on interference Alignment and the interference elimination method of dynamic power distribution, nearly close to the QPSK under ecotopia in terms of performance of BER Modulating system, multipoint cooperative ZF precoding and do not carry out power distribution (constant power distribution) interference alignment performance close, Method proposed by the invention during high s/n ratio multipoint cooperative to be significantly better than ZF precoding, has under identical bit error rate The performance boost of 3-4dB.
Fig. 6 and Fig. 7 be algorithms of different up to rate correlation curve, comparison other is proposed by the invention based on sky line selection Select, interference alignment and the interference elimination method of dynamic power distribution, and based on sky line options, the interference elimination side of interference alignment Method, multipoint cooperative ZF precoding algorithms based on sky line options, and do not carry out the non-cooperating ZF precoding of day line options Algorithm.Simulation result shows, the non-cooperating ZF pre-coding system not carrying out day line options is interference-limited, based on sky line selection The cooperation ZF precoding selected is optimum, and interference alignment schemes based on constant power distribution is close.The method of the present invention Non-cooperating ZF method for precoding relatively has obviously advantage, and up in rate performance after adding dynamic allocation algorithm There is certain loss, but loss is less, be about relative to the performance loss when 4 antenna of multipoint cooperative ZF method for precoding 3bits/sec/Hz, when 8 antenna, performance loss is about 5bits/sec/Hz, and this still falls within tolerance interval.Because the present invention The part that the complexity versus Multi-Point cooperation method for precoding of institute's extracting method is much lower, the most complicated in institute of the present invention extracting method For Eigenvalues Decomposition that matrix size is N × N and matrix inversion operation, complexity is O (N3), and multipoint cooperative ZF prelists Code needs to carry out the inversion operation of global channel matrix, and computation complexity is O ((KN)3), wherein K is total number of users.
The above, the only detailed description of the invention of the present invention, any feature disclosed in this specification, unless especially Narration, all can be by other equivalences or have the alternative features of similar purpose and replaced；Disclosed all features or all sides Method or during step, in addition to mutually exclusive feature and/or step, all can be combined in any way.

Claims (1)

1. based on sky line options and the multiple cell extensive MIMO interference elimination method of interference alignment, it is characterised in that under including Row step:
Step 1: base station end obtains channel matrix Hij, wherein user identifier j=1,2,3, base station identifier i=1,2,3, and Hij For N × Metzler matrix, wherein N is the number of antennas of user side, and M is the number of antennas of base station end；
Step 2: based on channel matrix Hij, base station end calculates the norm of the column vector corresponding to each transmitting antenna respectively, selects model The front Ns root antenna of number maximum is as active antenna, and closes residue M-NsRoot antenna；
Step 3: base station end is according to from channel matrix HijColumn vector corresponding to middle selection Ns root active antenna is as new channel Matrix H _ asij；
Step 4: base station end is according to channel matrix H _ asijCalculate the interference alignment precoding vector v of each base stationi:
401: to confederate matrixCarry out Eigenvalues Decomposition, the D row that selected characteristic value is maximum Characteristic vector is as the interference alignment precoding vector v of base station 11Row vector of going forward side by side normalized, wherein D is the data sent Flow amount；I.e. v1(:, r)=v1(:,r)/||v1(:, r) | |, r=1 ..., D, symbol (:, r) expression takes r column operations；
402: according to formulaThe interference alignment precoding vector v of calculation base station 22Row vector of going forward side by side normalization Process；
403: according to formulaThe interference alignment precoding vector v of calculation base station 3.3Row vector of going forward side by side normalization Process；
Step 5: base station end is according to formula wj=U_Hj((j-1) * D+1:j*D :) calculates the reception of user j and compels null vector wj, its InAndSymbol ()HTable Show the conjugate transpose of matrix；
Step 6: base station end compels null vector w based on receivingjDistribute transmit power p of each data streamjr, i.e. WhereinP represents the total emission power of all base stations, djrRepresenting matrix djR The value of the nonzero element of row, symbol diag () represents asks for diagonal；
Step 7: according to transmit power p of step 6 distributionjrMore newly received ZF vector, evenIts Middle pj=diag (pj1,pi2,...,pjD)；
Step 8: current base station end i generates and is sent to user j transmission data xjAnd send, wherein xj=vi*pj*sj, described sjTable Show the originally transmitted data being sent to user j.
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Cited By (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106341169A (en) * 2016-10-25 2017-01-18 重庆大学 Antenna selection method for the uplink of multi-user large-scale MIMO system
CN107104715A (en) * 2017-06-07 2017-08-29 南京邮电大学 A kind of interference alignment schemes based on day line options
CN107135544A (en) * 2017-04-06 2017-09-05 杭州电子科技大学 A kind of efficiency resource allocation methods updated based on interference dynamic
CN107566018A (en) * 2017-09-02 2018-01-09 西安电子科技大学 Multiple cell MIMO IMAC delay CSIT interference alignment schemes
CN108964734A (en) * 2018-06-29 2018-12-07 电子科技大学 A kind of antenna selecting method for nonlinear precoding
US10708924B2 (en) 2018-02-22 2020-07-07 Trabus Technologies Data communication using interference alignment

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103067062A (en) * 2013-01-23 2013-04-24 西安电子科技大学 Base station antenna selecting method based on interference alignment in multi-cell system
CN103166685A (en) * 2013-02-04 2013-06-19 重庆邮电大学 Interference aligning method based on combined power distribution in LTE
CN103780356A (en) * 2014-02-21 2014-05-07 上海师范大学 Design method for two-level precodes of cognitive MIMO communication system
CN104540209A (en) * 2014-12-01 2015-04-22 国家电网公司 Method for improving transmission rate of interference alignment network
CN105007108A (en) * 2015-07-03 2015-10-28 北京邮电大学 Distributed interference alignment method based on transmit antenna selection

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103067062A (en) * 2013-01-23 2013-04-24 西安电子科技大学 Base station antenna selecting method based on interference alignment in multi-cell system
CN103166685A (en) * 2013-02-04 2013-06-19 重庆邮电大学 Interference aligning method based on combined power distribution in LTE
CN103780356A (en) * 2014-02-21 2014-05-07 上海师范大学 Design method for two-level precodes of cognitive MIMO communication system
CN104540209A (en) * 2014-12-01 2015-04-22 国家电网公司 Method for improving transmission rate of interference alignment network
CN105007108A (en) * 2015-07-03 2015-10-28 北京邮电大学 Distributed interference alignment method based on transmit antenna selection

Cited By (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106341169A (en) * 2016-10-25 2017-01-18 重庆大学 Antenna selection method for the uplink of multi-user large-scale MIMO system
CN106341169B (en) * 2016-10-25 2019-09-06 重庆大学 A kind of antenna selecting method of the extensive mimo system uplink of multi-user
CN107135544A (en) * 2017-04-06 2017-09-05 杭州电子科技大学 A kind of efficiency resource allocation methods updated based on interference dynamic
CN107104715A (en) * 2017-06-07 2017-08-29 南京邮电大学 A kind of interference alignment schemes based on day line options
CN107104715B (en) * 2017-06-07 2020-06-12 南京邮电大学 Interference alignment method based on antenna selection
CN107566018A (en) * 2017-09-02 2018-01-09 西安电子科技大学 Multiple cell MIMO IMAC delay CSIT interference alignment schemes
CN107566018B (en) * 2017-09-02 2020-04-14 西安电子科技大学 Delay CSIT interference alignment method of multi-cell MIMO-IMAC
US10708924B2 (en) 2018-02-22 2020-07-07 Trabus Technologies Data communication using interference alignment
CN108964734A (en) * 2018-06-29 2018-12-07 电子科技大学 A kind of antenna selecting method for nonlinear precoding

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